Articles | Volume 12, issue 2
https://doi.org/10.5194/os-12-417-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-12-417-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
River bulge evolution and dynamics in a non-tidal sea – Daugava River plume in the Gulf of Riga, Baltic Sea
Edith Soosaar
CORRESPONDING AUTHOR
Marine Systems Institute at Tallinn University of
Technology, Tallinn, Estonia
Ilja Maljutenko
Marine Systems Institute at Tallinn University of
Technology, Tallinn, Estonia
Rivo Uiboupin
Marine Systems Institute at Tallinn University of
Technology, Tallinn, Estonia
Maris Skudra
Marine Systems Institute at Tallinn University of
Technology, Tallinn, Estonia
Urmas Raudsepp
Marine Systems Institute at Tallinn University of
Technology, Tallinn, Estonia
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Cited articles
Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamical
processes of the UCLA General Circulation Model, Meth. Comput. Phys., 17,
173–263, 1977.
Attila, J., Koponen, S., Kallio, K., Lindfors, A., Kaitala, S., and
Ylöstalo, P.: MERIS Case II water processor comparison on coastal sites
of the northern Baltic Sea, Remote Sens. Environ., 128, 138–149,
2013.
Avicola, G. and Huq, P.: The characteristics of the recirculating bulge
region in coastal buoyant outflows, J. Mar. Res., 61,
435–463, 2003.
BSHC (Baltic Sea Hydrographic Commission): Baltic Sea Bathymetry Database
version 0.9.3., available at: http://data.bshc.pro/ (last access: 8 March 2016),
2013.
Beltrán-Abaunza, J. M., Kratzer, S., and Brockmann, C.: Evaluation of MERIS products
from Baltic Sea coastal waters rich in CDOM, Ocean Sci., 10, 377–396, https://doi.org/10.5194/os-10-377-2014, 2014.
Burchard, H. and Bolding, K.: GETM – a general estuarine transport model,
Scientific documentation, Technical Report EUR 20253 EN, European
Commission, 2002.
Burchard, H. and Rennau, H.: Comparative quantification of physically and
numerically induced mixing in ocean models, Ocean Modelling, 20,
293–311, 2008.
Chant, R. J., Wilkin, J., Zhang, W., Choi, B.-J., Hunter, E., Castelao, R.,
Glenn, S., Jurisa, J., Schofield, O., Houghton, R., Kohut, J., Frazer, T. K.,
and Moline, M. A.: Dispersal of the Hudson River plume in the New York Bight:
Synthesis of observational and numerical studies during LaTTE, Oceanography,
21, 148–161, 2008.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach,
H., Holm, E. V., Isaksen, L., Kallberg, P., Köhler, M., Matricardi, M.,
McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de
Rosnay, P., Tavolato, C., Thepaut, J.-N., and Vitart, F.: The ERA-Interim
reanalysis: configuration and performance of the data assimilation system,
Q. J. Roy. Meteor. Soc., 137, 553–597, 2011.
Doerffer, R. and Schiller, H.: The MERIS case 2 water algorithm.
Int. J. Remote Sens., 28, 517–535, 2007.
Doerffer, R. and Schiller, H.: MERIS Regional Coastal and Lake Case 2 Water
Project atmospheric correction ATBD (Algorithm Theoretical Basis Document),
1.0, 41 pp., 2008.
Doerffer, R., Sorensen K., and Aiken, J.: MERIS potential for coastal zone
applications, Int. J. Remote Sens., 20, 1809–1818,
1999.
Dzwonkowski, B. and Yan, X.: Tracking of a Chesapeake Bay estuarine outflow
plume with satellite-based ocean color data, Cont. Shelf Res.,
25, 1942–1958, 2005.
Fernández-Nóvoa, D., Mendes, R., Decastro, M., Dias, J.,
Sánchez-Arcilla, A., and Gómez-Gesteira, M.: Analysis of the
influence of river discharge and wind on the Ebro turbid plume using
MODIS-Aqua and MODIS-Terra data, J. Marine Syst., 142, 40–46,
2015.
Fong, D. A. and Geyer, W. R.: The Alongshore Transport of Freshwater in a
Surface-Trapped River Plume, J. Phys. Oceanog., 32, 957–972, 2002.
Funkquist, L. and Kleine, E.: An introduction to HIROMB, an operational
baroclinic model for the Baltic Sea, Tech. Rep. SMHI, Norrköping, 2000.
Gitelson, A. A., Gurlin, D., Moses, W. J., and Barrow, T.: A bio-optical
algorithm for the remote estimation of the chlorophyll-a concentration in
case 2 waters, Environ. Res. Lett., 4, 045003
https://doi.org/10.1088/1748-9326/4/4/045003, 2009.
Goyens, C., Jamet, C., and Schroeder, T.: Evaluation of four atmospheric
correction algorithms for MODIS-Aqua images over contrasted coastal waters,
Remote Sens. Environ., 131, 63–75, 2013.
Gräwe, U., Holtermann, P., Klingbeil, K., and Burchard, H.: Advantages of
vertically adaptive coordinates in numerical models of stratified shelf
seas, Ocean Model., 92, 56–68, 2015.
Gregorio, S. O., Haidvogelb, D. B., Thomasa, P. J., Taskinogluc, E. S., and
Skeend, A. J.: Laboratory and numerical simulations of gravity-driven coastal
currents: Departures from geostrophic theory, Dynam. Atmos. Oceans, 52,
20–50, 2011.
Hetland, R. D. and Signell, R. P.: Modelling coastal current transport in the
Gulf of Maine, Deep-Sea Res. II, 52, 2430–2449, 2005.
Hopkins, J., Lucas, M., Dufau, C., Sutton, M., Stum, J., Lauret, O., and
Channelliere, C.: Detection and variability of the Congo River plume
from satellite derived sea surface temperature, salinity, ocean colour and
sea level, Remote Sens. Environ., 139, 365–385, 2013.
Horner-Devine, A. R.: The bulge circulation in the Columbia River plume,
Cont. Shelf Res., 29, 234–251, 2009.
Horner-Devine, A. R., Fong, D. A., Monismith, S. G., and Maxworthy, T.:
Laboratory experiments simulating a coastal river inflow, J. Fluid Mech.,
555, 203–232, 2006.
Horner-Devine, A. R., Fong, D. A., and Monismith, S. G.: Evidence for the
inherent unsteadiness of a river plume: Satellite observations of the
Niagara River discharge, Limnol. Oceanogr., 53, 2731–2737, 2008.
Horner-Devine, A. R., Hetland, R., and Macdonald, D.: Mixing and Transport in
Coastal River Plumes, Annu. Rev. Fluid Mech., 47, 569–594, 2015.
Keruss, M. and Sennikovs, J.: Determination of tides in Gulf of Riga and
Baltic Sea. Proc. International Scientific Colloqium “Modelling of Material
Processing”, Riga, 28–29 May 1999.
Klingbeil, K., Mohammadi-Aragh, M., Gräwe, U., and Burchard, H.:
Quantification of spurious dissipation and mixing discrete variance decay in
a finite-volume frame-work, Ocean Model., 81, 49–64, 2014.
Kudela, R. M., Horner-Devine, A. R., Banas, N. S., Hickey, B. M., Peterson,
T. D., Lessard, E. J., Frame, E., Bruland, K. W., Lohan, M., Jay, D. A.,
Peterson, J., Peterson, B., Kosro, M., Palacios, S., and Dever, E. P.:
Multiple trophic levels fueled by recirculation in the Columbia River plume,
Geophys. Res. Lett., 37, L18607, https://doi.org/10.1029/2010GL044342, 2010.
Lips, U., Zhurbas, V., Skudra, M., and Väli, G.: A numerical study of
circulation in the Gulf of Riga, Baltic Sea. Part I: Whole-basin gyres and
mean currents, Cont. Shelf Res., 112, 1–13, 2016.
Maljutenko, I. and Raudsepp, U.: Validation of GETM model simulated long-term
salinity fields in the pathway of saltwater transport in response to the
Major Baltic Inflows in the Baltic Sea, in: IEEE Xplore: Baltic International
Symposium (BALTIC), 2014 IEEE/OES, 27–29 May 2014, Tallinn Estonia, IEEE,
23–31, 2014.
Mendes, R., Vaz, N., Fernández-Nóvoa, D., Silva, J., Decastro, M.,
Gómez-Gesteira, M., and Dias, J.: Observation of a turbid plume using
MODIS imagery: The case of Douro estuary (Portugal), Remote Sens. Environ., 154, 127–138, 2014.
Nof, D. and Pichevin, T.: The Ballooning of Outflows, J. Phys. Oceanogr.,
31, 3045–3058, 2001.
Pan, J., Gu, Y., and Wang, D.: Observations and numerical modeling of the
Pearl River plume in summer season, J. Geophys. Res.-Oceans, 119,
2480–2500, 2014.
Pietrzak, J.: The use of TVD limiters for forward-in-time upstream-biased
advection schemes in ocean modeling, Mon. Weather Rev., 126, 812–830, 1998.
Raudsepp, U.: Interannual and seasonal temperature and salinity variations in
the Gulf of Riga and corresponding saline water inflow from the Baltic
Proper, Nordic Hydrology, 32, 135–160, 2001.
Raudsepp, U., Beletsky, D., and Schwab, D. J.: Basin-scale topographic waves
in the Gulf of Riga, J. Phys. Oceanogr., 33, 1129–1140,
2003.
Saldías, G., Sobarzo, M., Largier, J., Moffat, C., and Letelier, R.:
Seasonal variability of turbid river plumes off central Chile based on
high-resolution MODIS imagery, Remote Sens. Environ., 123, 220–233,
2012.
Shchepetkin, A. F. and McWilliams, J. C.: A method for computing horizontal
pressuregradient force in an oceanic model with a nonaligned vertical
coordinate, J. Geophys. Res., 108, 3090, https://doi.org/10.1 029/2001JC001047, 2003.
Siitam, L., Sipelgas, L., and Uiboupin, R.: Analysis of natural background
and dredging-induced changes in TSM concentration from MERIS images near
commercial harbours in the Estonian coastal sea, Int. J. Remote Sens., 35, 6764–6780, 2014.
Stips, A., Bolding, K., Pohlmann, T., and Burchard, H.: Simulating the
temporal and spatial dynamics of the North Sea using the new model GETM
(general estuarine transport model, Ocean Dyn., 54, 266–283, 2004.
Soosaar, E., Hetland, R. D., Horner-Devine, A., Avener, M. E., and Raudsepp,
U.: Offshore spreading of buoyant bulge from numerical simulations and
laboratory experiments. In: IEEE Xplore: Baltic International Symposium
(BALTIC), 2014 IEEE/OES, 27–29 May 2014, Tallinn Estonia, IEEE,
2014a.
Soosaar, E., Maljutenko, I., Raudsepp, U., and Elken, J.: An investigation of
anticyclonic circulation in the southern Gulf of Riga during the spring
period, Cont. Shelf Res., 78, 75–84, 2014b.
Thomas, P. J. and Linden, P. F.: Rotating gravity currents: small-scale and
large-scale laboratory experiments and a geostrophic model, J. Fluid Mech.,
578, 35–65, 2007.
Umlauf, L. and Burchard, H.: Second-order turbulence closure models for
geophysical boundary layers. A review of recent work, Cont. Shelf Res., 2,
795–827, 2005.
Undén, P., Rontu, L., Jörvinen, H., Lynch, P., Calvo, J., Cats, G.,
Cuxart, J., Eerola, K., Fortelius, C., Garcia-Moya, J. A., Jones, C.,
Lenderink, G., McDonald, A., McGrath, R., Navascues, B., Nielsen, N. W.,
Ødegaard, V., Rodrigues, E., Rummukainen, M., Rõõm, R., Sattler,
K., Sass, B. H., Savijörvi, H., Schreur, B. W., and Sigg, R., The, H.,
and Tijm, A.: HIRLAM-5 scientific documentation, available at:
http://www.hirlam.org/ (last access: 8 March 2016), 2002.
Vaičiūtė, D., Bresciani, M., and Bučas, M.: Validation of
MERIS Bio-Optical Products with In Situ Data in the Turbid Lithuanian Baltic
Sea Coastal Waters, J. Appl. Remote Sens., 6,
063568-1–063568-20, https://doi.org/10.1117/1.JRS.6.063568, 2012.
Valente, A. and Silva, J.: On the observability of the fortnightly cycle of
the Tagus estuary turbid plume using MODIS ocean colour images, J. Marine Syst., 75, 131–137, 2009.
Whitney, M. and Garvine, R.: Wind influence on a coastal buoyant outflow, J. Geophys. Res., 110,
C03014, https://doi.org/10.1029/2003JC002261, 2005.
Yankovsky, A. E. and Chapman, D. C.: A simple theory for the fate of buoyant
coastal discharges, J. Phys. Oceanogr., 27, 1386–1401, 1997.
Short summary
Remote sensing imagery and numerical model study of river bulge evolution and dynamics in a non-tidal sea showed an anti-cyclonically rotating bulge during the studied low wind period in the Gulf of Riga. In about 7–8 days the bulge grew up to 20 km in diameter, before being diluted. Both model and satellite images showed river water mainly contained in the bulge. The study shows significant effects of the wind in the evolution of the river bulge, even if the wind speed was moderate (3–4 m s−1).
Remote sensing imagery and numerical model study of river bulge evolution and dynamics in a...